i Detection of Smoke and Dust Aerosols Using Multi-sensor Satellite ...

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Relative change of L1B (%) 0.25 0.2 0.15 0.1 0.05 0.1 Scan direction Track direction 0.09 0 0 500 Frame 1000 Figure. 7.6: The relative change of L1B measurements with different BBR shift (1, 2, and 3 pixels). Relative change of L1B (%) 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 1 pixel shift 2 pixels shift 3 pixels shift Figure. 7.7: The relative change of L1B measurement in the percentage with various SZA shift (left image: positive SZA shift; right image: negative SZA shift) 111 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 0 500 1000 Row 1500 2000 The relative change of L1B with different SZA shift 0 0.01 o SZA shift 0.03 o SZA shift 0.05 o SZA shift 0.1 o SZA shift 0.2 -1.8 -0.05 0 0 20 40 60 80 -2 0 20 40 60 80 SZA (degree) o SZA shift -0.1 o SZA shift -0.2 -0.4 -0.6 -0.8 -1 -1.2 -1.4 -1.6 -0.01 o SZA shift -0.03 o SZA shift
7.2.1.2 Real Impact on L1B Measurement The SZA science dataset in the L1A file usually has a 1 km spatial resolution. The interpolation is necessary because on-orbit BBR shifts of all bands are less than one pixel in both MODIS instruments. The simplest method, linear interpolation, is adopted. The relative errors of L1B dataset caused by using uncorrected SZA for all Aqua MODIS RSBs except band 1 are listed in Table 7.2, where the largest SZA is up to 68 0 . The third and fourth columns provide the relative errors in scan or track direction individually, and the last column presents the relative errors by combining errors in two directions together. Since the relative error is proportional to the spatial BBR shift, those SMIR bands which have larger BBR shifts also have larger relative errors. The relative errors of Terra MODIS bands are less than those of Aqua MODIS bands due to their smaller BBR shifts. The largest relative error of L1B dataset is less than 0.1%. The error is small enough to be ignored, so far, in real applications for both MODIS instruments. 7.2.2 Impact analysis of mis-registration on science data products The MODIS is of great importance in science research field, widely used for applications in atmosphere, land, ocean, biosphere, and solid earth (Justice et al., 1998; Esaias et al, 1998; King ea al., 2003; Parkinson et al., 2003). A series of data products have been developed so far for various applications including a bunch of normalized indices and products generated with the linear or non-linear combination of responses from several spectral bands. The spatial mis-registration between different bands or FPAs impacts obviously the precision of science data products when several bands combined 112
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Detection of Smoke and Dust Aerosol
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DEDICATION This is dedicated to my
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TABLE OF CONTENTS Page LIST OF TABL
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LIST OF TABLES Table Page Table 1.1
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Figure 6.2 The UVAI images and the
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VFM Vertical Feature Mask VIS Visib
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are validated not only visually wit
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1.1 Importance of Studying Smoke an
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1.3 Objectives and Scopes The main
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originalities, and discussions of f
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1.6 Principal Results The principle
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CHAPTER 2 REVIEW OF APPROACHES FOR
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cooperatively: the reflectance at 0
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more information about dust charact
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CHAPTER 3 SMOKE AEROSOL DETECTION W
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with a two-side scan mirror which r
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3.1.2 MODIS data The 55 0 scan angl
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Sun Satellite Figure 3.2: Basic rad
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1 0 /2 b ( 0 0, 0; , ) k1 e
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3.2.3 Training data collection Surf
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Reflectance Reflectance Response cu
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Figure 3.6: The normalized ratio of
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all pixels over both land and ocean
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NDDI 1 0.8 0.6 0.4 0.2 0 -0.2 Figur
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MODIS L1B measurements Pixels over
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is clear that most of smoke plumes
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a b c b Figure 3.10: Smoke images o
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3.4.2 California 2007 fire The 2007
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The multi-spectral approach is test
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4.1 Physical Principle of Dust Aero
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Aqua 2006 102-04/12 04:15 Terra 200
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The dust has a high reflectivity at
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0.55 0.5 0.45 0.4 0.35 0.3 0.25 0.2
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7 a Dust pixel 0.5 b 6 Cloud pixel
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4.3 Results Three dust events occur
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c c Figure 4.6: Dust storm over TAK
Page 74: 4.4 Chapter Summary In this chapter
Page 77 and 78: operated in the A-train orbit with
Page 79 and 80: 5.1.2 CALIPSO measurements and VFM
Page 81 and 82: Altitude (km) 20 15 10 5 UTC: 2006-
Page 83 and 84: After spatial registration, the ove
Page 85 and 86: Figure 5.4(a) The MODIS true color
Page 87 and 88: Altitude (km) BTD (K) 20 15 10 15 4
Page 89 and 90: in the same A-train orbit with simi
Page 91 and 92: Aqua spacecrafts are operated in th
Page 93 and 94: the Fig. 6.1a. For easy comparison,
Page 95 and 96: esolutions, the number of smoke pix
Page 97 and 98: 6.1.4 Validation of dust monitoring
Page 99 and 100: Figure 6.3 Validation of dust image
Page 101 and 102: eflectance in red band. Therefore,
Page 103 and 104: Altitude (km) 20 15 10 5 UTC: 2006-
Page 105 and 106: image at the same location. The rea
Page 107 and 108: accuracy could be increased further
Page 109 and 110: FPAs and cold FPAs (because of diff
Page 111 and 112: development of future remote sensin
Page 113 and 114: Figure 7.3: SRCA spatial mode retic
Page 115 and 116: 7.1.3.2 Date Source MODIS L1B data
Page 117 and 118: characterization. Only the measurem
Page 119 and 120: these bands, including reflective s
Page 121 and 122: different spectral bands are slight
Page 123: SZA (Degree) SZA (Degree) 65 60 55
Page 127 and 128: 7.2.2.1 Theoretical impact analysis
Page 129 and 130: spatial characterization, the bigge
Page 131 and 132: Difference NDDI with spatial correc
Page 133 and 134: 8.1 Conclusions CHAPTER 8 CONCLUSIO
Page 135 and 136: Based on the detection results, the
Page 137 and 138: 3) Validating aerosol detection qua
Page 139 and 140: REFERENCES Ackerman, S. A., 1989, U
Page 141 and 142: imagery, Atmospheric Environment, v
Page 143 and 144: Salomonson, V. V., Privette, J. L.,
Page 145 and 146: Martinez, A., and Gros, G., 2007-10
Page 147 and 148: Wang W., Qu, J. J., Liu, Y., Hao, X
Page 149: CURRICULUM VITAE Yong Xie is a Ph.D
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